Packt.-.R.Bioinformatics.Cookbook.2019.Retail.EPUB.eBook-BitBook
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- 2020-03-21
NFO
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| R Bioinformatics Cookbook |
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| DATE: 21-03-2020 SIZE: 8.24 MB DISKS: 1x50.00MB PAGES: n/a |
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| PUBLISHER: n/a GENRE: |
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| AUTHOR: Dan MacLean |
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| FORMAT: EPUB PROTECTION: DRM EDITION: n/a |
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| URL: https://is.gd/T4q7js |
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| LANGUAGE: English ISBN: 9781789950694 |
: :
: Over 60 recipes to model and handle real-life biological data using modern :
: libraries from the R ecosystem Key Features Apply modern R packages to :
: handle biological data using real-world examples Represent biological data :
: with advanced visualizations suitable for research and publications Handle :
: real-world problems in bioinformatics such as next-generation sequencing, :
: metagenomics, and automating analyses Book Description Handling biological :
: data effectively requires an in-depth knowledge of machine learning :
: techniques and computational skills, along with an understanding of how to :
: use tools such as edgeR and DESeq. With the R Bioinformatics Cookbook, :
: you'll explore all this and more, tackling common and not-so-common :
: challenges in the bioinformatics domain using real-world examples. This :
: book will use a recipe-based approach to show you how to perform practical :
: research and analysis in computational biology with R. You will learn how :
: to effectively analyze your data with the latest tools in Bioconductor, :
: ggplot, and tidyverse. The book will guide you through the essential tools :
: in Bioconductor to help you understand and carry out protocols in RNAseq, :
: phylogenetics, genomics, and sequence analysis. As you progress, you will :
: get up to speed with how machine learning techniques can be used in the :
: bioinformatics domain. You will gradually develop key computational skills :
: such as creating reusable workflows in R Markdown and packages for code :
: reuse. By the end of this book, you'll have gained a solid understanding o :
: the most important and widely used techniques in bioinformatic analysis an :
: the tools you need to work with real biological data. What you will learn :
: Employ Bioconductor to determine differential expressions in RNAseq data :
: Run SAMtools and develop pipelines to find single nucleotide polymorphisms :
: (SNPs) and Indels Use ggplot to create and annotate a range of :
: visualizations Query external databases with Ensembl to find functional :
: genomics information Execute large-scale multiple sequence alignment with :
: DECIPHER to perform comparative genomics Use d3.js and Plotly to create :
: dynamic and interactive web graphics Use k-nearest neighbors, support :
: vector machines and random forests to find groups and classify data Who :
: this book is for This book is for bioinformaticians, data analysts, :
: researchers, and R developers who want to address intermediate-to-advanced :
: biological and bioinformatics problems by learning through a recipe-based :
: approach. Working knowledge of R programming language and basic knowledge :
: of bioinformatics are prerequisites. :
. :
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Files
| Path | Size |
|---|
| bb-r.bioinformatics.cookbook.nfo | 11,40 KB |
| bbquzd1a.zip | 8,21 MB |